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    The Nine Pillars Of Industry 40: Technological Advancements

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    • Ali kidwaiContent Architect
      The goal is to turn data into information, and information into insights.
    20-January-2021
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    • Manufacturing
    • Data Analytics
    • Data Science

    Editor's Note: In today's rapidly evolving technological landscape, understanding the essence of Industry 4.0 technologies and its transformative potential is crucial for businesses across various sectors. This illuminating blog unravels the concept of Industry 4.0 and its fundamental principles. It explores how the convergence of manufacturing 4.0 technologies is reshaping industries, revolutionizing production processes, and unlocking new levels of efficiency and innovation.

    Introduction

    Advancements in technology have driven dramatic increases in industrial productivity since the rise of the Industrial Revolution. The steam engine powered factories in the 19th century, electrification led to significant production in the early part of the 20th century, and industry became automated in the 1970s.

    This transition is so compelling that the fourth industrial revolution will combine sophisticated manufacturing methods and activities with smart systems incorporated into individuals, organizations, & resources.

    This revolution is marked by the emergence of new technologies such as analytics, robotics, AI, Generative AI, nanotechnology, cognitive technologies, IoT, and more. Companies need to define the techniques that better fulfill their requirements related to investment.

    If organizations do not understand the changes and opportunities that Industry 4.0 brings, they run the risk of losing market share.

    Why Is Industry 4.0 Crucial?

    It is essential to understand the potential of this fourth industrial revolution because it will affect manufacturing processes. Its range is much broader, involving all industries and sectors. Industry 4.0 can improve revenue growth, and business operations, and transforms the supply chain, products, and customer expectations. Such a change will likely modify the way we do things.

    According to McKinsey, technologies like GenAI when coupled with Industry 4.0 can lead to delivering productivity with a value ranging from 10%-15% of overall R&D costs of new services and products.

    Technologies coupled with Industry 4.0 can lead to entirely new services and products. The use of portable devices and sensors, robotics, and analysis will allow improvements in products in numerous ways, from creating tests and prototypes to the integration of connectivity to previously disconnected products.

    Now that we know the importance of AI in Industry 4.0 let's look at the core pillars of this technological revolution.

    9 Pillars Of Technological Advancements

    The 9 Industry 4.0 pillars are advancements that bridge the digital and physical worlds and make autonomous and smart systems possible. Supply chains and businesses are already using some of these innovative technologies, but the full completion of Industry 4.0 comes at the front when used together.

    1. Big Data And Analytics

    AI in Industry 4.0 based on Industrial data and analytics has come out recently in the manufacturing world where it optimizes production quality, improves equipment service, and saves energy. Big data analytics in Industry 4.0 is in the context that the comprehensive evaluation and collection of data from many different sources production equipment and systems and organization- and CMS—will become standard to support decision-making in real-time.

    For example, Infineon Technologies, a semiconductor manufacturer has reduced product failures by correlating single-chip data encapsulated in the testing phase at the end of the production process with process data collated in the wafer status phase in the early process. In this way, industry 4.0 analytics helped Infineon to quickly identify patterns that assist them in discharging faulty chips early in the production process and improved product quality.

    2. Autonomous Robots

    Manufacturers in numerous industries have used robots to tackle complex assignments, but now they’re progressing towards greater utility. They are becoming more flexible, autonomous, and cooperative. And hence, they will interact and work safely with humans and learn from them. These robots and analytics chatbots will be economical and have a more excellent range of capabilities than those used in manufacturing today.

    For example, Kuka, a European robotic equipment manufacturer, offers autonomous robots that interact. These robots are interconnected to work together and automatically adjust their actions to fit the next unfinished product in the line. Control units and High-end sensors enable close collaboration with humans.

    3. Industrial Internet Of Things (IIoT)

    In the current scenario, only some of a manufacturer's machines and sensors are networked and make use of embedded computing. The Industrial Internet of Things is so central to Industry 4.0 that the two terms are used interchangeably. Most of the physical things in Industry 4.0 – devices, machinery, robots, products, equipment, - use sensors to provide real-time data about their performance, condition, or location.

    This technology lets organizations run smoother supply chains, rapidly modify, and design products, stay on top of consumer preferences, prevent equipment downtime, track products and inventory, and much more.

    A drive-and-control-system vendor, Bosch Rexroth, outfitted a production facility for valves with a decentralized production and semi-automated process. Products are identified by identification codes, radiofrequency and workstations to know which manufacturing steps must be performed for each product and can adapt to perform the specific operation.

    4. Simulation/ Digital Twin

    A digital twin is a virtual simulation of a real-world product, machine, system, or process based on IoT sensor data. Though used interchangeably, digital twins and stimulation are slightly different since a digital twin uses real-time data (from sensors) and runs multiple stimulations. It allows businesses to better analyze, understand, and improve the maintenance and performance of products and industrial systems. Supported by high-performance computing for complex stimulation, manufacturers can create virtual replicas of products and factories in real-time. And to add up to the capabilities AI takes it to the next step, connecting this predictability to practicality. For instance, an asset operator can use a digital twin to identify a specific malfunctioning part. And along with AI – predict potential issues, and improve uptime.

    The German machine-tool vendor Siemens developed a virtual machine that can simulate the machining of parts utilizing the data from the physical machine. This shredded the setup time for the actual machining process by as much as 80 percent.

    5. Augmented Reality

    Augmented-reality-based systems support various services, like sending repair instructions over mobile devices and selecting parts in a warehouse. These systems are currently in their infancy, but in the coming time, organizations will make much broader use of AR to provide workers with real-time information to improve decision-making and work procedures.

    For instance, Siemens has developed a virtual plant-operator training module for its Comos software that uses a realistic, data-based 3-D environment with AR glasses to training their plant personnel to handle emergencies.

    6. Additive Manufacturing

    Organizations have begun to adopt additive manufacturing, such as 3-D printing, mostly to produce individual components and prototypes. Having Industry 4.0 in place, these additive-manufacturing methods will be widely used to make small batches of customized products that offer construction advantages, like high performance, lightweight designs, and more.

    For example, aerospace organizations are using additive manufacturing to apply new designs that reduce aircraft weight and lower expenses for raw materials such as titanium.

    Adding to this, AI will have a profound impact on addictive manufacturing. From proactive quality assurance and defect detection to Predictive maintenance, AI enables heightened maintenance and inventory efficiency. This helps manufacturers shift from proactive quality assurance. Further predictive maintenance helps them to analyze equipment lifecycle and anticipate maintenance needs using historical data.

    7. Cybersecurity

    Numerous organizations still rely on production systems and management, and that is disconnected or closed. With the use of standard communications protocols and increased connectivity with Industry 4.0, the need to protect manufacturing lines and critical industrial systems from cybersecurity threats increases drastically. As a result, reliable and secure communications and access management of machines and users are a must.

    During the past year, various industrial equipment vendors have joined forces with cybersecurity companies through partnerships or acquisitions.

    8. Cloud Computing

    Cloud computing is the "great enabler" of digital transformation. In the present scenario, cloud technology goes way beyond scalability, speed, cost efficiencies, and storage. It gives the foundation for the most advanced technologies – from AI and ML to the IoT – and provides organizations with a way to organize. The data that power Industry 4.0 cloud computing technologies reside in the cyber-physical systems and the cloud at the core of Industry 4.0 use the cloud to coordinate and communicate.

    As experts in providing comprehensive Azure cloud solutions, we have observed that businesses supported by strong cloud computing solutions benefit from scalability, speed, cost efficiencies, and improved storage.

    9. Horizontal And Vertical System Integration

    Most of the functions in the organization still are not fully integrated. And to do so, what’s needed is end-to-end visibility from plants to products to automation. But at present most of the manufacturing IT systems lack complete integration. Due to this organizations, customers, and suppliers are rarely closely linked.

    Currently, most of the IT systems are not fully integrated. Organizations, customers and suppliers are rarely closely linked. Functions in the organization are not fully integrated. From plants to products to automation—lacks complete integration.

    But with Industry 4.0 technologies organizations, functions, departments, and capabilities will become much more tenacious, as cross-organization, universal data-integration networks evolve and enable a truly automated value chain. To do so, people are realizing the need for a platform that facilitates connected planning and collaboration.

    Let's take an example; Boost AeroSpace and Dassault Systems launched a collaboration platform that serves as a common workspace for manufacturing and design collaboration and is available as a service on a private cloud. It manages all the tricky tasks of exchanging product and production data among multiple partners.

    Tired of siloed data and hindering your planning process? Find out how Polestar Solutions helps businesses with connected planning solutions.

    The Future

    The connectivity promoted by Industry 4.0 paves a path for promising opportunities. The Universal Robots chief technology officer and co-founder, explained, "Industry 5.0 will make the factory a place where creative people can come and work, to create a more personalized and human experience for workers and their customers." By connecting how machines and man work together, estimates say that Industry 5.0 will mean that over 60% of manufacturing, logistics and supply chains, agri-farming, and the mining and oil and gas sectors will employ chief robotics officers by 2025.

    Therefore, it can be said that Industry 4.0 is more than just technology. It is about making fundamental changes in how manufacturing is done. There are new manufacturing industries and new manufacturing processes to go along with all the latest technology. It is about doing new things, creating new products, and providing capabilities that didn't exist anywhere just a few years ago.

    About Author

    Big data analytics
    Ali kidwai

    Content Architect

    The goal is to turn data into information, and information into insights.

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    • Manufacturing
    • Data Analytics
    • Data Science

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